Avatars are widely used in various systems and applications, such as computer games, user interface applications, and telecommunications (e.g., in FaceTime provided by Apple iPhone 4, and in Avatar Kinect provided by Microsoft Xbox 360).
For instance, an avatar (e.g., a real face, a cartoon face, an animal face, etc.) simulates a user's facial expressions and head movements. Not only does this provide an interesting user experience, this can protect the user's privacy when the user does not want to reveal his or her real face.
Additionally, using an avatar to replace a real face can save considerable communications bandwidth. This allows for the efficient execution of collaborative applications (e.g., video conferencing, virtual classrooms, etc.).
There are three general problems associated with facial expression driven avatar applications. First, it is hard for a camera to accurately capture and track changes in a human's facial expressions when varying illumination conditions and head movements exist. Second, camera-based face tracking can only reliably track a limited number of facial features (e.g., 10 points such as mouth corners, eye corners, and so forth). Such a limited number may be inadequate to directly wholly drive avatar facial expression animations. Third, to describe real facial expression changes need a lot of communication bandwidth, which is a barrier for applications like video conference or avatar based communications.